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Deconvolution of hemodynamic response from fMRI data
Bartoň, Marek ; Kolář, Radim (referee) ; Havlíček, Martin (advisor)
This paper deals with the variability of HRF, which may have crucial impact on outcomes of fMRI neuronal activation detection in some cases. There are three methods described - averaging, regression deconvolution and biconjugate gradient method - which provide HRF shape estimation. In frame of simulations regression method, which uses B-spline curves of 4-th order for window length of 30 s, was chosen as the most robust method. Deconvolution estimates was used as HRF models for classic analyse of fMRI data, concretely visual oddball paradigm, via general linear model. Enlargement of localizated areas was observed and after expert consultation with scientific employees from neurology clinic, outcomes was evaluated as relevant. Furthermore Matlab application, which provides confortable observation of HRF variability among brain areas, was made.
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Restoration of optical coherence tomography image data
Smékal, Ondřej ; Odstrčilík, Jan (referee) ; Jan, Jiří (advisor)
Restoration of image data has become an essential part of the processing of medical images obtained by any system. The same applies in the case of optical coherence tomography. The aim of this work is to study the first restoration methods. Second, the description of the data representation from optical coherence tomography and subsequent discussions that restoration methods based on deconvolution would potentially find application in processing of Optical coherence tomography. Finally, the third to create a program solution of the OCT data restoration process in MATLAB environment and followed by discussion of effectiveness of the presented solutions.
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Implementation of restoring method for reading bar code
Kadlčík, Libor ; Bartušek, Karel (referee) ; Mikulka, Jan (advisor)
Bar code stores information in the form of series of bars and gaps with various widths, and therefore can be considered as an example of bilevel (square) signal. Magnetic bar codes are created by applying slightly ferromagnetic material to a substrate. Sensing is done by reading oscillator, whose frequency is modulated by presence of the mentioned ferromagnetic material. Signal from the oscillator is then subjected to frequency demodulation. Due to temperature drift of the reading oscillator, the demodulated signal is accompanied by DC drift. Method for removal of the drift is introduced. Also, drift-insensitive detection of presence of a bar code is described. Reading bar codes is complicated by convolutional distortion, which is result of spatially dispersed sensitivity of the sensor. Effect of the convolutional distortion is analogous to low-pass filtering, causing edges to be smoothed and overlapped, and making their detection difficult. Characteristics of convolutional distortion can be summarized into point-spread function (PSF). In case of magnetic bar codes, the shape of the PSF can be known in advance, but not its width of DC transfer. Methods for estimation of these parameters are discussed. The signal needs to be reconstructed (into original bilevel form) before decoding can take place. Variational methods provide effective way. Their core idea is to reformulate reconstruction as an optimization problem of functional minimization. The functional can be extended by other functionals (regularizations) in order to considerably improve results of reconstruction. Principle of variational methods will be shown, including examples of use of various regularizations. All algorithm and methods (including frequency demodulation of signal from reading oscillator) are digital. They are implemented as a program for a microcontroller from the PIC32 family, which offers high computing power, so that even blind deconvolution (when the real PSF also needs to be found) can be finished in a few seconds. The microcontroller is part of magnetic bar code reader, whose hardware allows the read information to be transferred to personal computer via the PS/2 interface or USB (by emulating key presses on virtual keyboard), or shown on display.
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Deconvolution in perfusion imaging
Líbal, Marek ; Havlíček, Martin (referee) ; Bartoš, Michal (advisor)
The purpose of this study is to introduce the methods of the deconvolution and to programme some of them. For the simulation, the tissue homogeneity model and the model of arterial input fiction were used. These models were engaged as the test procedures with the aim of verify the functionality and utility of the Wiener filter, the Lucy-Richardson algorithm and the Singular value decomposition.
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Three-Dimensional Reconstruction of Image in Digital Holographic Microscopy
Týč, Matěj ; Karásek,, Vítězslav (referee) ; Martišek, Dalibor (referee) ; Chmelík, Radim (advisor)
This thesis deals with the topic of 3D image processing for digital holographic microscopy - numerical refocusing. This method allows to perform mathematically accurate defocus correction on image of a sample captured away from the sample plane and it was applicable only for images that were made made using coherent illumination source. It has been generalized to a form in which it is also applicable to devices that use incoherent (non-monochromatic or extended) illumination sources. Another presented achievement concerns hologram processing. The advanced hologram processing method enables obtaining more data mainly concerning precision of quantities from one hologram — normally, one would have to capture multiple holograms to get those. Both methods have been verified experimentally.
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Design of magnetic bar-code read head
Kadlčík, Libor ; Drexler, Petr (referee) ; Mikulka, Jan (advisor)
Magnetic bar-code is composed from ferromagnetic bars printed on a substrate. The amount of ferromagnetic material is low, therefore reading magnetic barcode requires sensitive methods. Principle of methods of sensing both low-intensity magnetic field (fluxgates) and detecting low concentration of ferromagnetic material (resonant circuit, differential sensor) will be described. There are sensors producing frequency-modulated signal, therefore we focus on frequency demodulators as well. Signal acquired by sensor suffers from convolution distortion, reconstruction methods will be introduced. The assembled device consists of sensing oscillator, frequency demodulator, amplifier and reconstructing circuit. Frequency demodulation is done by phase-locked loop or differential demodulator. Reconstruction is based on detection of inflection points, producing square signal (representing bars of barcode). Design of these blocks is described. The device is able to read magnetic barcodes and reconstruct convolutionary distorted acquired signal. The differential demodulator exhibits low noise and low temperature drift (contrary to phase-locked loop). Signal produced by reading 2 mm wide bars is reconstructed without any problems, bars of width less than 1 mm cause troubles in certain cases (due to high degree of convolution distortion).
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Odstranění rozmazání pomocí dvou snímků s různou délkou expozice
Sabo, Jozef ; Šroubek, Filip (advisor) ; Horáček, Jan (referee)
In the presented work we study methods of image deblurring using two images of the same scene with different exposure times, focusing on two main approach categories, the so called deconvolution and non-deconvolution methods. We present theoretical backgrounds on both categories and evaluate their limitations and advantages. We dedicate one section to a comparison of both method categories on test data (images) for which we use a MATLAB implementation of the methods. We also compare the effectiveness of said methods against the results of a selected single- image de-noising algorithm. We do not focus at computational efficiency of algorithms and work with grayscale images only.
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Odstranění rozmazání pomocí dvou snímků s různou délkou expozice
Sabo, Jozef ; Šroubek, Filip (advisor) ; Horáček, Jan (referee)
In the presented work we study the methods of image deblurring using two images of the same scene with different exposure times, focusing on two main approach categories, so called deconvolution and non-deconvolution methods. We present theoretical backgrounds on both categories and evaluate their limitations and advantages. We dedicate one section to compare both method categories on test data (images) for which we our MATLAB implementation of the methods. We also compare the effectiveness of said methods against the results of a selected single-image de-noising algorithm. We do not focus at computational efficiency of algorithms and work with single-channel images only.
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Image Deblurring in Demanding Conditions
Kotera, Jan ; Šroubek, Filip (advisor) ; Portilla, Javier (referee) ; Jiřík, Radovan (referee)
Title: Image Deblurring in Demanding Conditions Author: Jan Kotera Department: Institute of Information Theory and Automation, Czech Academy of Sciences Supervisor: Doc. Ing. Filip Šroubek, Ph.D., DSc., Institute of Information Theory and Automation, Czech Academy of Sciences Abstract: Image deblurring is a computer vision task consisting of removing blur from image, the objective is to recover the sharp image corresponding to the blurred input. If the nature and shape of the blur is unknown and must be estimated from the input image, image deblurring is called blind and naturally presents a more difficult problem. This thesis focuses on two primary topics related to blind image deblurring. In the first part we work with the standard image deblurring based on the common convolution blur model and present a method of increasing robustness of the deblur- ring to phenomena violating the linear acquisition model, such as for example inten- sity clipping caused by sensor saturation in overexposed pixels. If not properly taken care of, these effects significantly decrease accuracy of the blur estimation and visual quality of the restored image. Rather than tailoring the deblurring method explicitly for each particular type of acquisition model violation we present a general approach based on flexible automatic...
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Použití gyroskopů a akcelerometrů k doostření fotografií pořízených mobilním telefonem
Šindelář, Ondřej ; Šroubek, Filip (advisor) ; Wilkie, Alexander (referee)
Long exposure handheld photography is coupled with the problem of blurring, which is difficult to remove without additional information. The goal of this work was to utilize motion sensors contained in modern smartphones to detect exact motion track of the image sensor during the exposure and then to remove the blur from the resulting photograph according to this data. A system was proposed which performs deconvolution using a kernel from the recorded gyroscope data. An implementation on Android platform was proved on a test smartphone device.
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